Triple
T12038579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eagle Creek Fire |
E286601
|
entity |
| Predicate | restitutionAmount |
P89737
|
FINISHED |
| Object | approximately 36.6 million US dollars |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: approximately 36.6 million US dollars | Statement: [Eagle Creek Fire, restitutionAmount, approximately 36.6 million US dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: restitutionAmount Context triple: [Eagle Creek Fire, restitutionAmount, approximately 36.6 million US dollars]
-
A.
reparationAmountPerPerson
Indicates the specific amount of reparations allocated or owed to each individual person involved.
-
B.
legalActionSettlementAmount
chosen
Indicates the monetary amount agreed upon or ordered to resolve a legal action or dispute.
-
C.
previousStandardAmount
Indicates the amount or value that was in effect under the immediately preceding standard or baseline before the current one.
-
D.
approximateNumberAwarded
Indicates the estimated quantity of awards or recognitions given in a particular context or event.
-
E.
civilJudgmentAmount
Indicates the monetary value ordered or determined in a civil court judgment between parties.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bac9e08190aa1a99c835f29542 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:47 p.m.